Independent Component Analysis of the Gamma Ray Spectrometer data of SELENE (Kaguya)

O. Forni*, O. Gasnault, B. Diez, C. d'Uston, S. Maurice, Nobuyuki Hasebe, O. Okudaira, N. Yamashita, S. Kobayashi, Y. Karouji, M. Hareyama, M. Kobayashi, R. C. Reedy, K. J. Kim

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

We analyze the spectra measured by the Gamma Ray Spectrometer (GRS) on board the SELENE satellite orbiting the Moon. The spectra consist in 8192 energy channels ranging from 0 to 12 MeV and exhibiting lines of interest (O, Mg, A1, Si, Ti, Ca, Fe, K, Th, and U) superposed on a continuum. We have also analysed the data with various multivariate techniques, one of them being the Independent Component Analysis. We have used the JADE algorithm for our analysis that we focused in the energy range from 750 to 3000 keV. We identify at least three meaningful components. The first one is correlated to the Thorium map. The corresponding correlation coefficient spectrum exhibits the lines of Thorium, Potassium and Uranium. The second component is clearly correlated with the Iron as shown on its corresponding spectrum. Finally the third component seems to be related to the altitude of the spacecraft. This work shows that maps of elements such as iron will be available with the GRS data by a purely statistical analysis.

Original languageEnglish
Title of host publicationWHISPERS '09 - 1st Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing
DOIs
Publication statusPublished - 2009
Externally publishedYes
EventWHISPERS '09 - 1st Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing - Grenoble
Duration: 2009 Aug 262009 Aug 28

Other

OtherWHISPERS '09 - 1st Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing
CityGrenoble
Period09/8/2609/8/28

Keywords

  • Gamma ray spectroscopy
  • Independent Component Analysis
  • SELENE

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Signal Processing

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